1. Joint Modeling
1.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
1.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.000 1.000
## LDevsum 1.000 1.003
## dh0 1.019 1.075
## dl0 1.022 1.103
## dl1 0.999 0.999
##
## Multivariate psrf
##
## 1.02
1.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
1.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 1352.00759 | 22867.9115 |
| DIC3 | 1235.35490 | 22863.4987 |
| PWAIC | 78.19537 | 289.0734 |
| WAIC | 1291.19604 | 22890.1171 |
2. Separate Modeling of High-Level
2.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
2.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 0.999 0.999
## dh0 0.999 0.999
##
## Multivariate psrf
##
## 0.999
2.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
2.4 WAIC results
| H0b | |
|---|---|
| DIC | 1399.58344 |
| DIC3 | 1260.42560 |
| PWAIC | 94.77333 |
| WAIC | 1332.68373 |
3. Separate Modeling for Low-level
3.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
3.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## LDevsum 1.000 1
## dl0 0.999 1
## dl1 1.001 1
##
## Multivariate psrf
##
## 1
3.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
3.4 WAIC results
| L1 | |
|---|---|
| DIC | 22743.9548 |
| DIC3 | 22831.1732 |
| PWAIC | 327.6456 |
| WAIC | 22868.1148 |